Contextual color quantization algorithm

M. P. Yu, K. C. Lo
{"title":"Contextual color quantization algorithm","authors":"M. P. Yu, K. C. Lo","doi":"10.1109/ICIAP.2001.957075","DOIUrl":null,"url":null,"abstract":"We propose an heuristic approach to color-quantize images with contextual information taken into consideration. The idea is to locate the regions of an image having the greatest need for colors, and allocate more quantization levels to them. We achieve this by scanning the elements of the input image in a way determined by their local intensity and select the color representatives that comprise the color map according to their local popularity. The overall performance of the color quantization algorithm is evaluated on representative set of artificial and real-world images. The results show a significant image quality improvement compared to some of the other color quantization schemes.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 11th International Conference on Image Analysis and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2001.957075","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

We propose an heuristic approach to color-quantize images with contextual information taken into consideration. The idea is to locate the regions of an image having the greatest need for colors, and allocate more quantization levels to them. We achieve this by scanning the elements of the input image in a way determined by their local intensity and select the color representatives that comprise the color map according to their local popularity. The overall performance of the color quantization algorithm is evaluated on representative set of artificial and real-world images. The results show a significant image quality improvement compared to some of the other color quantization schemes.
上下文颜色量化算法
我们提出了一种启发式方法,考虑到上下文信息的颜色量化图像。这个想法是定位图像中最需要颜色的区域,并为它们分配更多的量化级别。我们通过扫描输入图像的元素,以一种由它们的局部强度决定的方式来实现这一点,并根据它们的局部流行度选择组成颜色图的颜色代表。在具有代表性的人工图像集和真实图像集上对颜色量化算法的总体性能进行了评价。结果表明,与其他一些颜色量化方案相比,图像质量得到了显著改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信